Identification of catalytic residues from protein structure using support vector machine with sequence and structural features

Ganesan Pugalenthi, K. Krishna Kumar, P. N. Suganthan*, Rajeev Gangal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Identification of catalytic residues can provide valuable insights into protein function. With the increasing number of protein 3D structures having been solved by X-ray crystallography and NMR techniques, it is highly desirable to develop an efficient method to identify their catalytic sites. In this paper, we present an SVM method for the identification of catalytic residues using sequence and structural features. The algorithm was applied to the 2096 catalytic residues derived from Catalytic Site Atlas database. We obtained overall prediction accuracy of 88.6% from 10-fold cross validation and 95.76% from resubstitution test. Testing on the 254 catalytic residues shows our method can correctly predict all 254 residues. This result suggests the usefulness of our approach for facilitating the identification of catalytic residues from protein structures.

Original languageEnglish (US)
Pages (from-to)630-634
Number of pages5
JournalBiochemical and biophysical research communications
Volume367
Issue number3
DOIs
StatePublished - Mar 14 2008
Externally publishedYes

Keywords

  • Active site
  • Functional residues
  • Protein function prediction
  • Sequence-structural features
  • Spatial neighbors

ASJC Scopus subject areas

  • Biophysics
  • Biochemistry
  • Molecular Biology
  • Cell Biology

Fingerprint

Dive into the research topics of 'Identification of catalytic residues from protein structure using support vector machine with sequence and structural features'. Together they form a unique fingerprint.

Cite this